purvit-vashishtha / Digit-Recognizer-App

App for MNIST Data using GitHub Pages.

Home Page:https://purvit-vashishtha.github.io/Digit-Recognizer-App/

Geek Repo:Geek Repo

Github PK Tool:Github PK Tool

Structure of App

keras - > Tensorflow.js ->(html + css + javascript)->github pages

Aim:

To make a convolution neural network to recognise handwritten digits by training the model on MNIST dataset available in keras.

MNIST DATASET:

The training dataset contain 60000 images and testing contain 10000 images. Each image is 28x28 pixel and grey scale.

CNN MODEL OVERVIEW:

⚈ It is a 17 layer model with Conv2D,MaxPooling2D,BatchNormalization,Dense,Flatten and Dropout layer combination.

⚈ Input layer has 32 neuron and output layer has 10 neurons as 10 different clases exsist.

⚈ 30 epochs are used.

⚈ Categorical_loss is loss function and adam is used for optimization.

⚈ Model gives 99.15% accuracy.

For Deployment:

Save model using tensorflowjs converters as json file and weight as .h5 file.Use Tensorflow.js to load model and predict in javascript file.

About

App for MNIST Data using GitHub Pages.

https://purvit-vashishtha.github.io/Digit-Recognizer-App/


Languages

Language:Jupyter Notebook 62.8%Language:JavaScript 20.0%Language:HTML 8.9%Language:CSS 8.2%